How AI makes work better

Increasingly, knowledge work requires a blend of human and machine
intelligence. How will your organization meet this challenge?

By Jeffrey Davis

Early next year, millions of Bank of America account holders will get
access to anew personal banker named
Erica. She’ll check account balances, make money transfers,
pay bills, and perform dozens of other tasks. Erica doesn’t get tired
or rude, and she’s on call 24/7.

As you probably guessed, Erica is a next‑generation chatbot, or
automated conversational agent. Unlike predecessor bots that primarily
answered questions, Erica can perform a variety of basic tasks in
response to voice commands.

True, you could handle most of those tasks by navigating the B of A
website, using its mobile app, or walking into a branch. But that’s
the point. Erica will make everyday banking easier, faster, and more
efficient. Michelle Moore, Bank of America's chief of digital banking,
claims that Erica is designed not to replace jobs,
but to help employees streamline complex tasks, such as building
better relationships with customers.

In recent years, the emergence of intelligent agents like Erica has
sparked fears that AI will replace human workers. This isn’t new.
Forty years ago, for example, the rise of ATMs sparked fears that bank
tellers were all headed for the breadline. In reality, as research by
economist James Bessen has
shown, the number of bank teller jobs actually increased after ATMs
became ubiquitous in the early 1990s.

So what happened? The number of tellers required per branch fell
because of ATMs. That reduced the cost of opening a new branch, with
the result that banks rushed to increase their footprints. Overall
growth in branch count drove aggregate job growth among tellers and
other branch employees.

Annual change in productivity since 1950

Worker productivity has tailed off significantly since the tech boom
of the late 1990s, despite mass adoption of cloud, mobile and social
technologies in recent years. Some economists believe AI will reverse
the trend and boost U.S. labor productivity by as much as 35 percent
by 2035.

At the same time, teller job descriptions changed from dispensing and
receiving cash to more complex services such as taking applications
for lines of processing mortgage payments. Recent forecasts see more
sophisticated bots and ATMs leading to fewer tellers, but that decline
will likely be offset by increased demand for roles such as financial
planning and personal account service. The U.S. Bureau of Labor
Statistics predicts that teller jobs will decline by 8% from 2016
through 2026, while personal financial advisor jobs will grow by 14%
over the same period.

Economists remain divided about the extent to which AI and related
technologies will replace human workers. In a 2017 survey of
economists by the University of Chicago Booth School of
Business, 26% of respondents believed AI technologies would
substantially increase the ranks of the long‑term unemployed in
advanced countries. Another 24% were uncertain, and 18% thought AI
would boost overall employment. And a recent study published by the National Bureau of Economic
Research predicted that robots would eventually replace
between three and six jobs per machine, with the burden falling more
heavily on lower‑wage workers.

No matter where the dust settles on net employment between man and
machine, it is the jobs themselves—and the nature of the work—that
will be changing soon. For example, a recent McKinsey
study found that fully half of all current work activities
can be automated by adapting technologies that exist today.

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In many cases, intelligent assistants like Erica will help knowledge
workers focus on more valuable and rewarding tasks. As MIT economist
Erik Brynjolfsson (co‑author of The Second Machine
Age) noted recently, “the most
effective rule for the new division of labor is rarely, if ever, ‘give
all tasks to the machine.’ Instead, if the successful completion of a
process requires 10 steps, one or two of them may become automated
while the rest become more valuable for humans to do.”

Take Amazon, for example. Three years ago, the company had just
1,400 robots operating in its warehouses. Today, it has over 50,000,
yet its hiring levels have stayed the same. By and large, the machines
aren’t displacing human workers. Instead they unburden employees from
robotic parts of the job—running products back and forth from shelf to
shelf—so they can focus on more valuable tasks.

Machine intelligence can help knowledge workers escape drudgery. In
ServiceNow’s 2017 State of Work
survey of executives at companies with at least 500
employees, respondents reported spending 16 hours per week in manual,
repetitive tasks such as answering email and requesting support
services. The survey also found that nine in 10 skilled employees
spend too much time on low‑value manual tasks.

Mark Purdy, chief economist with Accenture Research, sees an
employment symbiosis emerging. “With machines to do more of what I
call the three Ds—dull, dirty, and dangerous work, this could free
people up to do more interesting and fulfilling jobs, which could lift
participation rates,” he says.

Adds Purdy: “There is also strong potential for AI to lift labor
participation by promoting more flexible forms of working and bringing
work to previously excluded groups or regions. People in remote areas
with few traditional employment opportunities could in the future work
in virtual offices or virtual factories, without ever having to leave
their home region.”

Parallels in history

The blending of human and machine intelligence in knowledge work is
part of an upward cycle of productivity that started with the
Industrial Revolution. For example, farming once dominated the labor
force, accounting for 38% of all U.S. employment in 1900. Then came
the tractor and the internal combustion engine, along with better
fertilizers and new irrigation technologies.

Today agriculture accounts for just 2.6% of the labor market, yet
agricultural output has soared. Even as the amount of land and labor
used in farming has declined steadily over the decades, total farm
output more than doubled between 1948 and 2015. In 1930, the average
American farmer could feed four people. Today, the same farmer can
feed 155 people on
average. Writing in the first AI Index Report,
published in December 2017, Udacity founder Sebastian Thrun explains
the history of modern agriculture this way: Technology simply “freed
up 98 percent of us to find different jobs.”

With AI and other technologies emerging now, many believe a similar
cycle of long‑term productivity will begin again, with technology
replacing many manual tasks, freeing us up to create economic value in
other ways. Case in point: Seventy‑five percent of the U.S. labor
force now works in offices. Yet a significant portion of
21st‑century office work remains highly repetitive, even at
the top tier or the org chart. As Thrun sees it, “AI technology can
learn the patterns in our repetitive work, and help us do work faster.”

Think augmentation, not automation

What applies to chatbots and bankers also applies to
cardiologists—and hundreds of other knowledge work roles across the
labor force. By applying advanced machine vision and deep learning
techniques to MRI imaging, the San Francisco‑based startup Arterys has
built a system that automatically calculates how much blood is
coursing through the human heart. That calculation might take nearly
an hour for the typical cardiologist to do manually. Arterys can
handle it in 15 seconds, and with greater accuracy. Arterys won’t
replace cardiologists, but it will give these busy doctors more
minutes to spend on higher‑value tasks such as interacting with
patients or performing surgery.

SEBASTIAN THRUN, Founder, Udacity

With this new revolution, I predict we will enter an era of
unprecedented human creativity.

The promise of general-purpose technology

We can expect to see the number of skills where AI beats humans
increasing rapidly as new AI systems evolve and learn to perform more
complex work. Because AI is a general‑purpose technology—just like
electricity, the steam engine, and the combustion engine were in
previous centuries—it will fuel similar waves of complementary
innovation. Accenture estimates
that AI could increase economic productivity by 40% and double
economic growth rates by 2035.

“Most organizations are still at an early stage of AI adoption,”
says Accenture’s Purdy, “but it is likely that significant
organizational changes will be needed to harness the full benefits of
AI—in terms of human resources, finance, data management, and
leadership.” The AI‑enabled company of the future, in other words, is
clearly a work in progress, but one that will significantly alter our
definitions of work itself.

Business technology journalist Jeffrey Davis was a founding
editor of Business 2.0 magazine and executive editor at CBS Interactive.